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SKU/Artículo: AMZ-1783988347
IPython Notebook Essentials
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.52 kg
0.52 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Compute scientific data and execute code interactively with NumPy and SciPyAbout This BookPerform Computational Analysis interactivelyCreate quality displays using matplotlib and Python Data AnalysisStep-by-step guide with a rich set of examples and a thorough presentation of The IPython NotebookWho This Book Is ForIf you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.What You Will LearnQuickly install and get started with IPython NotebookCreate interactive widgets in the NotebookMaster the Notebook's interface and navigation featuresCreate publication-quality graphs and displays of data with matplotlibAdd media to the Notebook with IPython's Rich Display SystemAccelerate code using NumbaPro and concurrent computingPerform advanced scientific computations with SciPyWork with data in the Notebook with pandasIn DetailIn data science, it is difficult to present interesting visual or technical content, as it involves scientific notations that are not easy to type in a normal document format. IPython provides a web-based UI called Notebook, which creates a working environment for interactive computing that combines code execution with computational documents. IPython Notebook makes the task simpler as it was developed for scientific programming to solve larger problems through a series of smaller programs. IPython Notebook is used to learn Python in a fun and interactive way and to do some serious parallel / technical computing.The book begins with an introduction to the efficient use of IPython Notebook for interactive computation. The book then focuses on the integration of technologies such as matplotlib, pandas, and SciPy. The book is aimed at empowering you to work with IPython Notebook for interactive computing, configuring it, creating your own notebooks / research documents. You will learn how IPython lets you perform efficient computations through examples with NumPy, data analysis with pandas, and visualization with matplotlib.
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